What Digital Sovereignty Means for Logistics

Supply chains are becoming more complex, more digital, and more interconnected. This also increases the demands on transparency, controllability, and risk management. After all, the more logistics processes depend on data, platforms, and automated systems, the more relevant a strategic question becomes.

This is exactly where digital sovereignty comes into play. The term is often associated with independence, self-sufficiency, or isolation. For logistics, however, this understanding falls short. Sovereignty means, rather, being able to make decisions independently, control data flows, and switch between technological options as needed. It thus describes not a fixed state, but a fundamental capability: namely, the ability to remain capable of acting.

Logistics does not operate within closed systems. Goods and merchandise move across company boundaries, and information flows accordingly between different companies, applications, and operating environments.

This interconnectedness is necessary because, without the exchange of data, it is virtually impossible to coordinate supply chains based on the division of labor. Sovereignty, therefore, cannot mean withholding information as a matter of principle or avoiding digital connections. The key is to provide data in a controlled manner and to grant access deliberately. Companies should be able to determine what data they share, with whom, for what purpose, and under what conditions.

Data sovereignty is therefore more than just a matter of information security. It directly affects whether a company can control its logistics data, track its use, and utilize it for its own process management.

Without this oversight, a structural risk arises: Although a company may have digitized and interconnected processes, it may not be able to adequately track how information is shared, processed, or used. Digitization alone, therefore, does not yet ensure controllability.

A common misconception is to equate sovereignty with complete independence. For digitally connected logistics, however, self-sufficiency would be neither a realistic nor a sensible goal. Companies collaborate with technology providers, platforms, logistics service providers, and other business partners, and these collaborations are an integral part of modern supply chains.

The key, therefore, is not to avoid every dependency. What is crucial is to consciously manage dependencies and maintain one’s own decision-making capacity. Two key capabilities should be emphasized here: decision-making capacity and the ability to switch. Data, technologies, and operations must be structured in such a way that companies can make independent decisions and, for example, migrate systems from one environment to another. Interchangeability, in turn, does not mean regularly switching providers, platforms, or systems, but rather having a realistic option for action. If a company is effectively no longer able to switch technologies or operating environments, a normal dependency becomes a limitation on its ability to exercise control.

This offers an important perspective for decision-makers: Not every dependency is inherently problematic. It becomes problematic, however, when alternatives are lacking, the consequences are not transparent, or changes would only be possible under disproportionate conditions.

Digital sovereignty cannot be achieved through a single technology or security measure, but rather on the basis of four interconnected levels.

1. Data sovereignty refers to control over information. Who owns the data? Who is allowed to use it? How is access controlled? And under what conditions can data be transferred or further processed?
2. Technological sovereignty focuses on the systems and architectures in use. Among other things, it is crucial whether technologies are interchangeable and whether data and applications can be transferred to other environments.
3. Operational autonomy encompasses the organizational aspects of IT operations. This includes questions regarding the operating organizations involved, the location of operational processes, and the storage of the necessary operational knowledge.
4. Legal sovereignty takes the legal framework into account. What matters is which companies and countries are involved in the provision of services and which jurisdictions thereby exert influence over data, systems, and operations.

Only by considering these four levels together can a robust overall picture be formed. A technically secure system may still involve operational or legal dependencies. Conversely, a defined data location alone is not sufficient if access rights, operational responsibility, or options for change remain unclear.

Technical mechanisms such as encryption or "bring-your-own-key" approaches can help ensure control over data. However, transparency regarding which operating organizations are involved, where operational processes take place, who can access information, and where relevant operational knowledge is stored is equally important.

Even modern technologies such as the cloud and artificial intelligence do not fundamentally contradict sovereign design. Digital sovereignty does not mean excluding these technologies. Rather, the goal is to be able to use them independently under transparent conditions.

For data with an appropriate protection and usage framework, AI can, for example, be operated in a public or commercial cloud. If a higher level of protection is required, an isolated operating environment in a data center may be considered. There are further gradations possible between these options.

The key question, therefore, is not whether to use the cloud or AI. Rather, it is necessary to determine which operating model is suitable for which data, processes, and security requirements. A nuanced approach prevents both a blanket rejection of modern technologies and their uncritical use.

For decision-makers in logistics and IT, addressing the issue of sovereignty does not begin with a single technology decision. The first step is to develop a shared understanding of existing data flows and dependencies.

Five guiding questions can help with this:

1. What data and systems are particularly critical for logistics management?
2. Who can access this data, and under what conditions?
3. Which technologies, operating organizations, countries, and jurisdictions are involved?
4. What realistic options are available when a change or migration is necessary?
5. What level of protection is actually required for each process?

These questions do not yet provide a complete target architecture. However, they highlight the areas where companies have the capacity to act and where their ability to exert control might be limited.